A problem today for many individuals, particularly practitioners in the disciplines involving information analysis, is the scarcity of time and/or resources to review the large volumes of information that are available and potentially relevant. Effective and timely use of such large amounts of information is often impossible using traditional approaches, such as lists, tables, and simple graphs. Tools that can help individuals automatically identify and/or understand the themes, topics, and/or trends within a body of information are useful and necessary for handling these large volumes of information. Many traditional text analysis techniques focus on selecting features that distinguish documents within a document group. However, these techniques may fail to select features that characterize or describe the majority or a minor subset of documents within the group. Furthermore, when the information is streaming and/or updated over time, the group is dynamic and can change significantly. Therefore, most of the current tools are limited in that they only allow information consumers to interact with snapshots of an information space that is often times continually changing.
Since most information sources deliver information streams, such as news syndicates and information services, and/or provide a variety of mechanisms for feeding the latest information by region, subject, and/or by user-defined search interests, when using traditional text analysis tools, new information that arrives can eclipse prior information. As a result, temporal context is typically lost with employing group-oriented text analysis tools that do not accommodate dynamic corpora. Accurately identifying and intelligently describing change in an information space requires a context that relates new information with old. Accordingly, a need exists for systems and computer-implemented processes for identifying features and determining feature associations within a group of documents, especially when the group of documents is dynamic and changes with time.